Suppose we would like to explore the question: Does it rain more in Tacoma, Washington or Seattle, Washington?

Fit and interpret a simple linear regression model of annual precipitation in Tacoma modeled on annual precipitation in Seattle to address this question. Explain why such an approach is reasonable, and to what extent it answers the question.

Do the same to address the question of whether it rains more in Tacoma, Washington or Portland, Oregon.

You may ignore the fact that this data set is a time series and pretend for the present that it is a simple random sample of years, with all years being independent of each other. We will explore the extent to which this is not true and some of the modeling ramifications of this in Project 28.

Background on the data set

This data set gives annual precipitation totals for Portland (OR), Tacoma (WA),
and Seattle (WA) for the years 1966-2006, precipitation being defined as: "Any form
of water particles-liquid or solid-that falls from the atmosphere and reaches the
ground."